The effect of channel interactions on speech recognition in cochlear implant subjects: predictions from an acoustic model.

Acoustic models that produce speech signals with information content similar to that provided to cochlear implant users provide a mechanism by which to investigate the effect of various implant-specific processing or hardware parameters independent of other complicating factors. This study compares speech recognition of normal-hearing subjects listening through normal and impaired acoustic models of cochlear implant speech processors. The channel interactions that were simulated to impair the model were based on psychophysical data measured from cochlear implant subjects and include pitch reversals, indiscriminable electrodes, and forward masking effects. In general, spectral interactions degraded speech recognition more than temporal interactions. These effects were frequency dependent with spectral interactions that affect lower-frequency information causing the greatest decrease in speech recognition, and interactions that affect higher-frequency information having the least impact. The results of this study indicate that channel interactions, quantified psychophysically, affect speech recognition to different degrees. Investigation of the effects that channel interactions have on speech recognition may guide future research whose goal is compensating for psychophysically measured channel interactions in cochlear implant subjects.

Duke Scholars

Author Leslie M. Collins Electrical and Computer Engineering